Director, AI Engineering

Key Responsibilities:

• Collaborate with stakeholders to ensure that technical strategies are in line with ABMs AI roadmap.
• Conduct comprehensive technical research on emerging AI/ML models and technologies to pinpoint viable solutions for development, MVP creation, and deployment.
• Spearhead MVP development and productization by rapidly prototyping and validating promising AI solutions.
• Align AI initiatives with business objectives by offering expert insights on feasibility, scalability, and integration.
• Oversee the development of machine learning models, including those for NLP, computer vision, and predictive analytics.
• Guarantee that AI models are robust, scalable, and optimized for real-world application.
• Lead research into state-of-the-art AI/ML methodologies for business functions or products, such as deep learning, reinforcement learning, and generative AI.
• Collaborate closely with DevOps to streamline the deployment of AI models into production environments. Establish MLops practice and guardrails
• Implement industry best practices for AI/ML pipelines, including model monitoring, versioning, and periodic retraining.
• Ensure seamless integration of AI models with cloud platforms like Azure (Synapse, ADF, Databricks).
• Establish and enforce ethical AI frameworks to promote fairness, mitigate bias, and maintain transparency in AI systems.
• Work with security teams to protect AI models and data from potential threats.
• Partner with key stakeholders to implement and measure the impact of AI solutions across various business functions.

Required Skills & Expertise:

• Machine Learning & AI: Deep learning, NLP, generative AI, predictive analytics, reinforcement learning.
• MLOps & AI Engineering: Model deployment, cloud-based AI solutions, automation, monitoring, and retraining.
• Cloud & Data Platforms: Azure (Synapse, ADF, Databricks), AWS, Google Cloud, Snowflake.
• Programming & Frameworks: Python, TensorFlow, PyTorch, Hugging Face, Scikit-learn, SQL.
• Expertise and knowledge of OpenAIs GPT models, Gemini, LLaMA, Alteryx.
• Big Data & Infrastructure: Spark, Kubernetes, Kafka, data lakes, and scalable AI architectures.
• AI Governance & Compliance: Ethical AI, bias mitigation, data privacy laws (GDPR, CCPA).

Preferred Qualifications:

• Masters degree in Computer science, Data Science, AI, Machine Learning, or a related field (PhD preferred).
• 12+ years of experience in AI, data science, or ML engineering.
• 5+ years in leadership roles, managing AI and data teams.
• Experience in deploying AI models at scale in enterprise settings.
• Effective communication skills to bridge the gap between AI research, engineering, and business stakeholders.

Benefit Information:

ABM offers a comprehensive benefits package.For information about ABMs benefits, visit:

ABM 2025 Employee Benefits | Staff & Management